Effect of Doppler radial Velocity data assimilation on the simulation of a typhoon

approaching Taiwan

Hsin-Hung Lin, Pay-Liam LinNational Central University, Taiwan

Wu and Kuo (1999) pointed out that the major problems of typhoon prediction in Taiwan are caused by: 1) inadequate observations 2) insufficient model resolution 3) the complicated influence of the CMR on airflow

Mesoscale precipitation patterns induced by typhoon circulation over complicated terrain are difficult to predict. Radar wind data assimilations are used to study possible improvements to this problem.

In this study, the potential improvement of short-term typhoon predictions near Taiwan, particularly the related rainfall forecasts over the mountainous island, using Doppler radial wind observations is explored.

Typhoon Case• 2004/8/24-25 Typhoon Aere• 15-hr maximum accumulated rainfall is 760 mm

Experiment Design• MM5 and 3D-VAR• 3 Nesting Domain • model resolutions are 45, 15 and 5 km• Assimilate Doppler Radial Velocity and GTS data

Radar Data Number

First 2 cyclesLast 3 cycles

Radar Site at 766 meter height

5 assimilation cycles4 km radar data resolutionMax. 3000-3500 data points in each cycles

fewer data Below 3 km

Radar Data Number at each Height

Typhoon Track

CTL & GTS

DRV & GADCTL &

GTS

The typhoon movement was deflected toward the south during the second assimilation cycle

When Typhoon moved closer to Taiwan, the simulated typhoon positions closer to the observed track.

Typhoon Intensity

CTL & GTS

DRV , GAD, RV3

25.5 hPa

the DRV, GAD and RV3 produced relatively better minimum SLP, implying a positive influence of the radar data assimilation on typhoon intensity.

In comparison with the CTL, the error of the simulated central SLP was reduced by about 25%

Typhoon Aere

CTL

GTS

DRV

GAD

RV3

2004/08/25 0300 UTC

Doppler wind data assimilation made the better simulation results of eye wall and rainband structure

Typhoon Aere

Doppler wind data assimilation led the better rainfall simulation and improve the under-prediction above 5 mm threshold.

TS and BIAS for 3-hr Rainfall at the last assimilation cycle

Sensitivity Test

Case Assimilated data (typical number of data points in domain 3)

SEN-NON NoneSEN-SFC Surface station data (37)SEN-SND Upper air soundings (6)SEN-DRV Doppler radial velocity (3664)SEN-DUR Dual-Radar retrieval wind, resolution 2km(3593)

In order to clarify the individual impact of different observation.

Follow GAD, and assimilate single kind of observation at the last cycle.Dual-Radar retrieval wind was added in addition.

Sensitivity Test

3km radar coverage

Dual-radar wind coverage

Radar Data Number at each Height Doppler Wind

Dual-Radar wind 2km

Dual-Rada wind 4km

Dual-radar wind coverage is smaller than Doppler radial wind and lack data above 6 km

Sensitivity Test

SEN-SFC SEN-SND

SEN-DRV SEN-DUR

Increment of Horizontal Wind of Assimilation Analysis at 700 hPa

Red: positive incrementBlue: negative incrementSEN-DRV and SEN-DUR had stronger cyclonic positive increment

Sensitivity TestThe cross section of u-wind Increment of Analysis

at latitude 24.6SEN-SFC SEN-SND

SEN-DRV SEN-DUR

A

Red: positive incrementBlue: negative increment

Dual-Radar wind increase the low level wind, but decrease high level wind.

Sensitivity Test

SEN-SFC SEN-SND

SEN-DRV SEN-DUR

Red: positive incrementBlue: negative increment

C

The typhoon center cross section of u-wind IncrementSEN-DRV had more symmetric wind structure than SEN-DUR.

Sensitivity Test

SEN-DUR

SEN-DRV

SEN-SND

Compare with Sounding (46715) at the north Taiwan

Low Level Wind Speed

SEN-DUR had the best analysis wind speed

SEN-DRV is secondary

Sensitivity Test

SEN-DURSEN-DRV

SEN-SFCSEN-SND

Simulation Typhoon intensityMinimum Sea Level Pressure

Doppler wind data assimilation descended 3 hpaDual-Radar wind data assimilation descended 2 hPa

Summary• The model predicted fields including sea level pressure,

wind and precipitation were improved with the additional observed wind information through Doppler radial velocity assimilation.

• When the typhoon center moved closer to Taiwan and the whole circulation of the core region could be observed, the typhoon tracks were predicted more correctly with radar data assimilation

• The typhoon intensity also was increased and revised about 25 % errors from non-assimilation simulation.

• The effects of dual-radar retrieval wind leads the best low level wind speed of typhoon over the land by the analysis of data assimilation. The radar radial wind has the more symmetrical adjustment of wind structures than the dual-radar wind.

Thank You